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Strategies to overcome challenges to smart sustainable logistics: a Bayesian-based group decision-making approach.
- Source :
- Environment, Development & Sustainability; May2024, Vol. 26 Issue 5, p11743-11770, 28p
- Publication Year :
- 2024
-
Abstract
- The logistics sector has seen rapid growth in the past few years due to globalization and the rise in demand for goods and commodities. With the exponential growth, managing logistics is becoming complex and challenging, often due to a lack of traceability. Also, its negative impacts on the environment have increased due to increased footprints, thus causing a threat to sustainability. Incorporating smart systems in the logistics sector is a possible solution to overcome these issues. But the incorporation of smart technologies in the logistics sector of a developing economy is often marred by various challenges. This study aims to identify and prioritize the challenges to smart sustainable logistics (SSL) and the multiple strategies that can help overcome these challenges. A framework comprised of 19 barriers to SSL and seven strategies for overcoming these barriers is established via a comprehensive literature study and practitioner discussions. The Bayesian best–worst method is implemented to examine the barriers to SSL, while the additive value function is used to rank the strategies. The results indicate that businesses must develop internet infrastructure and R&D and innovation competencies for the logistics sector to be smart and sustainable. They also need to build institutional structures for technology development. Also, reducing technological uncertainties, enhancing research & development capabilities, and nurturing human resources in smart technologies can help logistics companies overcome these challenges. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1387585X
- Volume :
- 26
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Environment, Development & Sustainability
- Publication Type :
- Academic Journal
- Accession number :
- 176910604
- Full Text :
- https://doi.org/10.1007/s10668-023-03477-6